Equities — Quantitative Finance Scripts

A collection of Python notebooks and scripts for equity screening, portfolio construction, algorithmic trading strategies, and time-series forecasting.

Scripts

Most Advanced

File	Description	Key Techniques
SARIMAX Forecasting.ipynb	Seasonal ARIMA with exogenous variables for time-series forecasting	SARIMAX, statsmodels, seasonal decomposition
QuantValueStrategy.ipynb	Ranks S&P 500 stocks by composite value score; outputs recommended trades	Multi-metric percentile scoring (P/E, P/B, P/FCF, EV/EBITDA), batch API calls, Excel output
QuantMomentumStrategy.ipynb	Ranks S&P 500 stocks by multi-timeframe price momentum	1/3/6/12-month return percentiles, composite HQM score, Excel output
MACD_strategy_code.py	Full MACD-based algorithmic trading strategy on GOOGL	EMA crossover, signal generation, position tracking, P&L calculation

Supporting Scripts

File	Description
SP500Screener.ipynb	Scrapes S&P 500 constituents from Wikipedia and downloads historical price data via yfinance
SP500EqualWeightTracker.ipynb	Calculates share allocations for an equal-weight S&P 500 index portfolio
FTSEScreener.ipynb	Scrapes FTSE 100 tickers from stockchallenge.co.uk
RandomWalkGenerator.ipynb	Simulates random walk price paths using numpy
InflationForecast.ipynb	CPI data retrieval via FRED API (work in progress)

Machine Learning

No machine learning models (e.g. Random Forest, neural networks) are used in this repository. SARIMAX is a classical statistical forecasting method, not ML.

Dependencies

• yfinance, pandas, numpy, scipy, matplotlib
• statsmodels (SARIMAX)
• requests, beautifulsoup4, xlsxwriter
• fredapi (InflationForecast)
• IEX Cloud API token required for QuantMomentumStrategy, QuantValueStrategy, SP500EqualWeightTracker
• AlphaVantage API key required for MACD_strategy_code.py